exp_007 visualizing crimes and stations

this notebook intends to provide a map representation of information DC bikeshare ridership. In particular, am interested in … where are stations, how they align with

library(gbfs)

Warning: package ‘gbfs’ was built under R version 4.3.2

library(here)
library(janitor)
library(tidyverse)
library(openmeteo)
library(lubridate)
library(sf) # working with simple features - geospatial

Warning: package ‘sf’ was built under R version 4.3.2Linking to GEOS 3.11.2, GDAL 3.7.2, PROJ 9.3.0; sf_use_s2() is TRUE

library(tmap)

Warning: package ‘tmap’ was built under R version 4.3.2Breaking News: tmap 3.x is retiring. Please test v4, e.g. with
remotes::install_github('r-tmap/tmap')

library(tidycensus)

Warning: package ‘tidycensus’ was built under R version 4.3.2

 df1= st_read(here("raw_data",
                     "Crime_Incidents_in_2022.geojson")) %>%
  clean_names()

Reading layer `Crime_Incidents_in_2022' from data source 
  `D:\ds\raw_data\Crime_Incidents_in_2022.geojson' using driver `GeoJSON'
Simple feature collection with 27137 features and 23 fields
Geometry type: POINT
Dimension:     XY
Bounding box:  xmin: -77.11364 ymin: 38.81467 xmax: -76.91002 ymax: 38.99491
Geodetic CRS:  WGS 84

tmap_mode("view")

tmap mode set to interactive viewing

tm_shape(df1)+
  tm_facets("offense")+
  tm_dots("offense", legend.show = FALSE)